Predicting qos in scheduled crowdsourcing

Authors:
Roman Khazankin;Daniel Schall;Schahram Dustdar
Affiliations:
Distributed Systems Group, Vienna University of Technology, Vienna, Austria;Distributed Systems Group, Vienna University of Technology, Vienna, Austria;Distributed Systems Group, Vienna University of Technology, Vienna, Austria
Venue:
CAiSE'12 Proceedings of the 24th international conference on Advanced Information Systems Engineering
Year:
2012

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Abstract

Crowdsourcing has emerged as a new paradigm for outsourcing simple for humans yet hard to automate tasks to an undefined network of people. Crowdsourcing platforms like Amazon Mechanical Turk provide scalability and flexibility for customers that need to get manifold similar independent jobs done. However, such platforms do not provide certain guarantees for their services regarding the expected job quality and the time of processing, although such guarantees are advantageous from the perspective of Business Process Management. In this paper, we consider an alternative architecture of a crowdsourcing platform, where the workers are assigned to tasks by the platform according to their availability and skills. We propose the technique for estimating accomplishable guarantees and negotiating Service Level Agreements in such an environment.